General Approach
Statistical Parameters
Note
that if two or more comparisons are planned, there are two kinds of
type I errors: experiment-wise and comparison-wise error rates. The
experiment-wise error rate is the probability of making at least one
type I error when testing a whole collection of comparisons. The
comparison-wise error rate is the probability of a type I error set
by the analyst for evaluating each comparison.
State the type I error
rate or level of significance (alpha-level) to be used for all analysis
and whether statistical tests will be one- or two-sided. An example
might be “All tests will be two-sided and considered statistically
significant if P<0.05”.
Describe how you will adjust the level of significance when testing ...
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